Professional profile: contact and workplace (Bulk)

Profiles

curl --request POST \
  --url https://api.explorium.ai/v1/prospects/profiles/bulk_enrich \
  --header 'Content-Type: application/json' \
  --header 'api_key: <api-key>' \
  --data '
{
  "prospect_ids": [
    "<string>"
  ],
  "request_context": null,
  "parameters": {}
}
'

import requests

url = "https://api.explorium.ai/v1/prospects/profiles/bulk_enrich"

payload = {
    "prospect_ids": ["<string>"],
    "request_context": None,
    "parameters": {}
}
headers = {
    "api_key": "<api-key>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {api_key: '<api-key>', 'Content-Type': 'application/json'},
  body: JSON.stringify({prospect_ids: ['<string>'], request_context: null, parameters: {}})
};

fetch('https://api.explorium.ai/v1/prospects/profiles/bulk_enrich', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.explorium.ai/v1/prospects/profiles/bulk_enrich",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'prospect_ids' => [
        '<string>'
    ],
    'request_context' => null,
    'parameters' => [
        
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json",
    "api_key: <api-key>"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.explorium.ai/v1/prospects/profiles/bulk_enrich"

	payload := strings.NewReader("{\n  \"prospect_ids\": [\n    \"<string>\"\n  ],\n  \"request_context\": null,\n  \"parameters\": {}\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("api_key", "<api-key>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.explorium.ai/v1/prospects/profiles/bulk_enrich")
  .header("api_key", "<api-key>")
  .header("Content-Type", "application/json")
  .body("{\n  \"prospect_ids\": [\n    \"<string>\"\n  ],\n  \"request_context\": null,\n  \"parameters\": {}\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.explorium.ai/v1/prospects/profiles/bulk_enrich")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["api_key"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"prospect_ids\": [\n    \"<string>\"\n  ],\n  \"request_context\": null,\n  \"parameters\": {}\n}"

response = http.request(request)
puts response.read_body

{
  "response_context": {
    "correlation_id": "<string>",
    "time_took_in_seconds": 123
  },
  "total_results": 123,
  "data": [
    {
      "prospect_id": "<string>",
      "data": {
        "full_name": "<string>",
        "first_name": "<string>",
        "last_name": "<string>",
        "country_name": "<string>",
        "region_name": "<string>",
        "city": "<string>",
        "linkedin": "<string>",
        "experience": [
          {}
        ],
        "skills": [
          "<string>"
        ],
        "interests": [
          "<string>"
        ],
        "age_group": "<string>",
        "education": [
          {}
        ],
        "company_name": "<string>",
        "company_website": "<string>",
        "company_linkedin": "<string>",
        "job_department_array": [],
        "job_level_array": [],
        "job_title": "<string>",
        "linkedin_url_array": [
          "<string>"
        ]
      }
    }
  ],
  "entity_id": "<string>"
}

{
  "detail": [
    {
      "loc": [
        "<string>"
      ],
      "msg": "<string>",
      "type": "<string>"
    }
  ]
}

POST

prospects

profiles

bulk_enrich

Profiles

curl --request POST \
  --url https://api.explorium.ai/v1/prospects/profiles/bulk_enrich \
  --header 'Content-Type: application/json' \
  --header 'api_key: <api-key>' \
  --data '
{
  "prospect_ids": [
    "<string>"
  ],
  "request_context": null,
  "parameters": {}
}
'

import requests

url = "https://api.explorium.ai/v1/prospects/profiles/bulk_enrich"

payload = {
    "prospect_ids": ["<string>"],
    "request_context": None,
    "parameters": {}
}
headers = {
    "api_key": "<api-key>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {api_key: '<api-key>', 'Content-Type': 'application/json'},
  body: JSON.stringify({prospect_ids: ['<string>'], request_context: null, parameters: {}})
};

fetch('https://api.explorium.ai/v1/prospects/profiles/bulk_enrich', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.explorium.ai/v1/prospects/profiles/bulk_enrich",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'prospect_ids' => [
        '<string>'
    ],
    'request_context' => null,
    'parameters' => [
        
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json",
    "api_key: <api-key>"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.explorium.ai/v1/prospects/profiles/bulk_enrich"

	payload := strings.NewReader("{\n  \"prospect_ids\": [\n    \"<string>\"\n  ],\n  \"request_context\": null,\n  \"parameters\": {}\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("api_key", "<api-key>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.explorium.ai/v1/prospects/profiles/bulk_enrich")
  .header("api_key", "<api-key>")
  .header("Content-Type", "application/json")
  .body("{\n  \"prospect_ids\": [\n    \"<string>\"\n  ],\n  \"request_context\": null,\n  \"parameters\": {}\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.explorium.ai/v1/prospects/profiles/bulk_enrich")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["api_key"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"prospect_ids\": [\n    \"<string>\"\n  ],\n  \"request_context\": null,\n  \"parameters\": {}\n}"

response = http.request(request)
puts response.read_body

{
  "response_context": {
    "correlation_id": "<string>",
    "time_took_in_seconds": 123
  },
  "total_results": 123,
  "data": [
    {
      "prospect_id": "<string>",
      "data": {
        "full_name": "<string>",
        "first_name": "<string>",
        "last_name": "<string>",
        "country_name": "<string>",
        "region_name": "<string>",
        "city": "<string>",
        "linkedin": "<string>",
        "experience": [
          {}
        ],
        "skills": [
          "<string>"
        ],
        "interests": [
          "<string>"
        ],
        "age_group": "<string>",
        "education": [
          {}
        ],
        "company_name": "<string>",
        "company_website": "<string>",
        "company_linkedin": "<string>",
        "job_department_array": [],
        "job_level_array": [],
        "job_title": "<string>",
        "linkedin_url_array": [
          "<string>"
        ]
      }
    }
  ],
  "entity_id": "<string>"
}

{
  "detail": [
    {
      "loc": [
        "<string>"
      ],
      "msg": "<string>",
      "type": "<string>"
    }
  ]
}

Description

The Bulk Professional Profile Enrichment API provides detailed professional and workplace insights for up to 50 prospects in a single request. This endpoint enables deep analysis of career history, education, and workplace affiliations. Key Benefits:

Retrieve bulk professional profiles including job history, skills, and education.
Enhance recruiting and sales efforts with verified workplace details.
Optimize segmentation and outreach using structured career insights.

How It Works

Input: Provide up to 50 prospect_id values, obtained from the Match Prospects endpoint.
Processing: The system retrieves verified professional details, including job history, education, and workplace affiliations.
Output: Returns structured data in the same order as the input, ensuring easy mapping.

Request Schema

Field	Type	Description
`prospect_ids`	Array	A list of up to 50 unique prospect IDs (Required)

Example Request (cURL)

Bash

curl --request POST \
     --url https://api.explorium.ai/v1/prospects/profiles/bulk_enrich \
     --header 'accept: application/json' \
     --header 'api_key: <your api key>' \
     --header 'content-type: application/json' \
     --data '{
  "prospect_ids": [
    "ee936e451b50c70e068e1b54e106cb89173198c4",
    "d668424ab4f6aaeeeb74248d56b8335383fd522b"
  ]
}'

Example Response

JSON

{
  "response_context": {
    "correlation_id": "6f7eeca192604c73ae5b5a07671ba438",
    "request_status": "success",
    "time_took_in_seconds": 0.454
  },
  "data": [
    {
      "prospect_id": "ee936e451b50c70e068e1b54e106cb89173198c4",
      "data": {
        "full_name": "Satya Nadella",
        "country_name": "united states",
        "region_name": "washington",
        "city": "seattle",
        "linkedin": "https://linkedin.com/in/ACoAAAEkwwAB9KEc2TrQgOLEQ-vzRyZeCDyc6DQ",
        "experience": [
          {
            "company": {
              "name": "university of chicago",
              "website": "uchicago.edu"
            },
            "title": {
              "levels": [
                null
              ],
              "name": "member board of trustees"
            },
            "start_date": "2018-01",
            "is_primary": false
          },
          {
            "company": {
              "name": "fred hutch",
              "website": "fredhutch.org"
            },
            "title": {
              "levels": [
                "director"
              ],
              "name": "board member"
            },
            "start_date": "2016-01",
            "end_date": "2022-01"
          },
          {
            "company": {
              "name": "microsoft",
              "website": "microsoft.com"
            },
            "title": {
              "levels": [
                "cxo"
              ],
              "name": "chairman and chief executive officer"
            },
            "start_date": "2014-02",
            "is_primary": true
          },
          {
            "company": {
              "name": "starbucks",
              "website": "starbucks.com"
            },
            "title": {
              "levels": [
                "director"
              ],
              "name": "board member"
            },
            "start_date": "2017-01",
            "end_date": "2024-01"
          },
          {
            "company": {
              "name": "the business council us",
              "website": "thebusinesscouncil.org"
            },
            "title": {
              "levels": [
                "cxo"
              ],
              "name": "chairman"
            },
            "start_date": "2021-01",
            "end_date": "2023-01"
          }
        ],
        "skills": null,
        "interests": null,
        "age_group": "41-50",
        "education": [
          {
            "degrees": [
              "masters degree"
            ],
            "majors": [
              "computer science"
            ],
            "minors": [],
            "school": {
              "name": "university of wisconsin milwaukee"
            }
          },
          {
            "start_date": "1994",
            "end_date": "1996",
            "minors": [],
            "school": {
              "name": "the university of chicago booth school of business"
            }
          },
          {
            "degrees": [
              "bachelors degree"
            ],
            "majors": [
              "electrical engineering"
            ],
            "minors": [],
            "school": {
              "name": "manipal institute of technology"
            }
          }
        ],
        "gender": "male",
        "company_name": "Microsoft",
        "company_website": "https://microsoft.com",
        "company_linkedin": "https://www.linkedin.com/company/microsoft",
        "job_department": null,
        "job_department_array": [
          "c-suite"
        ],
        "job_department_main": "c-suite",
        "job_seniority_level": "cxo",
        "job_level_array": [
          "c-suite"
        ],
        "job_level_main": "c-suite",
        "job_title": "Chairman And Chief Executive Officer",
        "linkedin_url_array": [
          "https://linkedin.com/in/acoaaaekwwab9kec2trqgoleq-vzryzecdyc6dq",
          "https://linkedin.com/in/satyanadella"
        ]
      }
    },
    {
      "prospect_id": "d668424ab4f6aaeeeb74248d56b8335383fd522b",
      "data": {
        "full_name": "Jensen Huang",
        "country_name": "united states",
        "region_name": "california",
        "city": "los altos hills",
        "linkedin": "https://linkedin.com/in/ACoAABMznFkB_XPgkYHnUl33kIHTWt1DtMAV6Pg",
        "experience": [
          {
            "company": {
              "name": "nvidia",
              "website": "nvidia.com"
            },
            "title": {
              "levels": [
                "cxo"
              ],
              "name": "founder and chief executive officer"
            },
            "start_date": "1993-01",
            "is_primary": true
          },
          {
            "company": {
              "name": "dennys",
              "website": "dennys.com"
            },
            "title": {
              "levels": [
                null
              ],
              "name": "dishwasher, busboy, waiter"
            },
            "start_date": "1978-01",
            "end_date": "1983-01"
          }
        ],
        "skills": [
          "management"
        ],
        "interests": null,
        "age_group": "61-70",
        "education": [
          {
            "degrees": [
              "bsee"
            ],
            "start_date": "1980",
            "end_date": "1984",
            "minors": [],
            "school": {}
          },
          {
            "degrees": [
              "msee"
            ],
            "start_date": "1990",
            "end_date": "1992",
            "minors": [],
            "school": {}
          }
        ],
        "gender": "male",
        "company_name": "Nvidia",
        "company_website": "https://nvidia.com",
        "company_linkedin": "https://www.linkedin.com/company/nvidia",
        "job_department": null,
        "job_department_array": [
          "c-suite"
        ],
        "job_department_main": "c-suite",
        "job_seniority_level": "cxo",
        "job_level_array": [
          "c-suite",
          "founder"
        ],
        "job_level_main": "c-suite",
        "job_title": "Founder And Chief Executive Officer",
        "linkedin_url_array": [
          "https://linkedin.com/in/acoaabmznfkb_xpgkyhnul33kihtwt1dtmav6pg",
          "https://linkedin.com/in/jenhsunhuang"
        ]
      }
    }
  ],
  "entity_id": null,
  "total_results": 2
}

Best Practices

Ensure valid prospect IDs to maximize data accuracy.
Use enriched profiles to refine candidate selection and outreach.
Monitor career movements to track professional growth trends.
Leverage structured education and skills data for talent and partnership analysis.

Bulk Professional Profile Output Signals

Signal	API Name	Description	Data Type Final
gender	Individual’s gender	Gender reported by the individual on their profile. If gender is not reported on profile, returned value is ‘null’.	string
city	Individual’s city of residence	Individual’s city of residence reported on profile.	string
country_name	Individual’s country of residence	Individual’s country of residence reported on profile.	string
region_name	Individual’s State / Region of residence	Individual’s state or region of residence reported on profile.	string
company_website	Individual’s workplace: company website	URL to the company website belonging to the individual’s workplace.	string
company_linkedin	Individual’s workplace: company LinkedIn® url	URL to the company LinkedIn® page belonging to the individual’s workplace.	string
linkedin	Individual’s LinkedIn® URL	URL of the individual’s LinkedIn® profile.	url
linkedin_url_array	LinkedIn® Identifier Array	A list of LinkedIn® profile URLs associated with the prospect. Each entry may include a standard public URL and/or a URN-based URL.	array[string]
age_group	Individual’s age group	Individual’s estimated age group.	string
experience	Individual’s work experience background	List of work experience background entries on the individual’s profile. May include: company name, company website, job title, seniority level, role, start date, end date, and more. Includes current work experience activities if listed.	array
education	Individual’s educational background	List of educational background entries on the individual’s profile. May include: institutions name, institutions website, degree category, major, start date, end date, and more. Includes current educational activities if listed.	array
interests	Individual’s interests	List of all interests reported by the individual on their profile.	array
skills	Individual’s skills	List of all skills reported by the individual on their profile.	array
job_title	Individual’s job title	Individual’s current job title listed on their professional profile.	string
job_department	Individual’s job department	Individual’s job department, derived from their current job title.	object
job_department_array	Job Department (Array)	All detected normalized job departments for the individual. Examples: retail, engineering, customer success, administration, education, security, healthcare, public service, partnerships, creative, strategy, real estate, procurement, IT, data, c-suite, manufacturing, support, logistics, product, sales, design, marketing, finance, R&D, trade, human resources, legal, operations.	array<string>
job_department_main	Job Department (Main)	Primary normalized job department selected from the detected departments (e.g., “engineering”). Examples of possible values: retail, engineering, customer success, administration, education, security, healthcare, public service, partnerships, creative, strategy, real estate, procurement, IT, data, c-suite, manufacturing, support, logistics, product, sales, design, marketing, finance, R&D, trade, human resources, legal, operations.	string
job_seniority_level	Individual’s seniority level	Individual’s top seniority level, derived from their current job title.	object
job_level_array	Job Level (Array)	All detected normalized job levels for the individual. Examples: manager, president, senior manager, owner, advisor, freelancer, junior, director, c-suite, board member, senior non-managerial, non-managerial, partner, vice president, founder.	array<string>
job_level_main	Job Level (Main)	Primary normalized job level selected from the detected levels (e.g., “senior non-managerial”). Examples of possible values: manager, president, senior manager, owner, advisor, freelancer, junior, director, c-suite, board member, senior non-managerial, non-managerial, partner, vice president, founder.	string
company_name	Individual’s workplace: company name	Name of the company the individual listed as their workplace.	string
full_name	Individual’s full name	First and last names associated with the individual, appended with a space.	string

Body Params - Try Me Example

prospect_ids: ee936e451b50c70e068e1b54e106cb89173198c4,
  57f9e5dac64d31d80e6e9432fe2c500d0bba2c01

Authorizations

api_key

string

header

required

Body

application/json

prospect_ids

string[]

required

Required array length: 1 - 50 elements

Pattern: ^[a-f0-9]{40}$

request_context

Request Context · object | null

Example:

null

parameters

Parameters · object | null

Response

Successful Response

This is base response model for all responses in partner service.

response_context

ResponseContext · object

required

Show child attributes

total_results

integer

required

data

ProspectsBulkEnrichRow[ProfilesOutputSchema] · object[]

Show child attributes

entity_id

Pattern: ^[a-f0-9]{32}$

Individual's social media presence (Bulk)Overview

⌘I

Explorium AgentSource

Partners

Professional profile: contact and workplace (Bulk)

Description

Body Params - Try Me Example

Authorizations

Body

Response

​Description

​Body Params - Try Me Example

Authorizations

Body

Response

Description

Body Params - Try Me Example